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     "text": [
      "C:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Temp\\ipykernel_7680\\3709128709.py:11: DtypeWarning: Columns (16,17,18,19,20,21) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  machine_measurements = pd.read_csv(machine_measurements_path)\n"
     ]
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     "text": [
      "Machine Measurements Dataset:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 800035 entries, 0 to 800034\n",
      "Data columns (total 33 columns):\n",
      " #   Column       Non-Null Count   Dtype \n",
      "---  ------       --------------   ----- \n",
      " 0   subject_id   800035 non-null  int64 \n",
      " 1   study_id     800035 non-null  int64 \n",
      " 2   cart_id      800035 non-null  int64 \n",
      " 3   ecg_time     800035 non-null  object\n",
      " 4   report_0     800034 non-null  object\n",
      " 5   report_1     601108 non-null  object\n",
      " 6   report_2     525908 non-null  object\n",
      " 7   report_3     393551 non-null  object\n",
      " 8   report_4     227550 non-null  object\n",
      " 9   report_5     122212 non-null  object\n",
      " 10  report_6     56125 non-null   object\n",
      " 11  report_7     22370 non-null   object\n",
      " 12  report_8     7261 non-null    object\n",
      " 13  report_9     2328 non-null    object\n",
      " 14  report_10    898 non-null     object\n",
      " 15  report_11    401 non-null     object\n",
      " 16  report_12    193 non-null     object\n",
      " 17  report_13    103 non-null     object\n",
      " 18  report_14    42 non-null      object\n",
      " 19  report_15    19 non-null      object\n",
      " 20  report_16    11 non-null      object\n",
      " 21  report_17    3 non-null       object\n",
      " 22  bandwidth    800035 non-null  object\n",
      " 23  filtering    800035 non-null  object\n",
      " 24  rr_interval  800035 non-null  int64 \n",
      " 25  p_onset      800035 non-null  int64 \n",
      " 26  p_end        800035 non-null  int64 \n",
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      " 28  qrs_end      800035 non-null  int64 \n",
      " 29  t_end        800035 non-null  int64 \n",
      " 30  p_axis       800035 non-null  int64 \n",
      " 31  qrs_axis     800035 non-null  int64 \n",
      " 32  t_axis       800035 non-null  int64 \n",
      "dtypes: int64(12), object(21)\n",
      "memory usage: 201.4+ MB\n"
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       "   subject_id  study_id  cart_id             ecg_time           report_0  \\\n",
       "0    10000032  40689238  6848296  2180-07-23 08:44:00       Sinus rhythm   \n",
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       "\n",
       "                            report_1                    report_2  \\\n",
       "0  Possible right atrial abnormality                         NaN   \n",
       "1  Possible right atrial abnormality                         NaN   \n",
       "2                                NaN  Normal ECG except for rate   \n",
       "3                                NaN                  Normal ECG   \n",
       "4                                NaN                         NaN   \n",
       "\n",
       "         report_3 report_4 report_5  ...                    filtering  \\\n",
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       "1  Borderline ECG      NaN      NaN  ...  60 Hz notch Baseline filter   \n",
       "2             NaN      NaN      NaN  ...  60 Hz notch Baseline filter   \n",
       "3             NaN      NaN      NaN  ...  60 Hz notch Baseline filter   \n",
       "4             NaN      NaN      NaN  ...              <not specified>   \n",
       "\n",
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      "\n",
      "Record List Dataset:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 800035 entries, 0 to 800034\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count   Dtype \n",
      "---  ------      --------------   ----- \n",
      " 0   subject_id  800035 non-null  int64 \n",
      " 1   study_id    800035 non-null  int64 \n",
      " 2   file_name   800035 non-null  int64 \n",
      " 3   ecg_time    800035 non-null  object\n",
      " 4   path        800035 non-null  object\n",
      "dtypes: int64(3), object(2)\n",
      "memory usage: 30.5+ MB\n"
     ]
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       "   subject_id  study_id  file_name             ecg_time  \\\n",
       "0    10000032  40689238   40689238  2180-07-23 08:44:00   \n",
       "1    10000032  44458630   44458630  2180-07-23 09:54:00   \n",
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       "\n",
       "                                       path  \n",
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   ],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "# File paths\n",
    "machine_measurements_path = \"machine_measurements.csv\"  \n",
    "record_list_path = \"record_list.csv\"                  \n",
    "data_dictionary_path = \"machine_measurements_data_dictionary.csv\"  \n",
    "\n",
    "# Load CSV files\n",
    "machine_measurements = pd.read_csv(machine_measurements_path)\n",
    "record_list = pd.read_csv(record_list_path)\n",
    "\n",
    "# Display basic information about the datasets\n",
    "print(\"Machine Measurements Dataset:\")\n",
    "display(machine_measurements.info())\n",
    "display(machine_measurements.head())\n",
    "\n",
    "print(\"\\nRecord List Dataset:\")\n",
    "display(record_list.info())\n",
    "display(record_list.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Missing values in Machine Measurements:\n"
     ]
    },
    {
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      "text/plain": [
       "subject_id          0\n",
       "study_id            0\n",
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       "report_5       677823\n",
       "report_6       743910\n",
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       "report_8       792774\n",
       "report_9       797707\n",
       "report_10      799137\n",
       "report_11      799634\n",
       "report_12      799842\n",
       "report_13      799932\n",
       "report_14      799993\n",
       "report_15      800016\n",
       "report_16      800024\n",
       "report_17      800032\n",
       "bandwidth           0\n",
       "filtering           0\n",
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      ]
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      "\n",
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     ]
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       "      <td>files/p1000/p10000117/s48446569/48446569</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800030</th>\n",
       "      <td>19999840</td>\n",
       "      <td>48683947</td>\n",
       "      <td>48683947</td>\n",
       "      <td>2164-09-12 12:28:00</td>\n",
       "      <td>files/p1999/p19999840/s48683947/48683947</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800031</th>\n",
       "      <td>19999840</td>\n",
       "      <td>41842293</td>\n",
       "      <td>41842293</td>\n",
       "      <td>2164-09-17 11:31:00</td>\n",
       "      <td>files/p1999/p19999840/s41842293/41842293</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800032</th>\n",
       "      <td>19999987</td>\n",
       "      <td>41190887</td>\n",
       "      <td>41190887</td>\n",
       "      <td>2145-11-02 19:54:00</td>\n",
       "      <td>files/p1999/p19999987/s41190887/41190887</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800033</th>\n",
       "      <td>19999987</td>\n",
       "      <td>45828463</td>\n",
       "      <td>45828463</td>\n",
       "      <td>2145-11-03 03:00:00</td>\n",
       "      <td>files/p1999/p19999987/s45828463/45828463</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800034</th>\n",
       "      <td>19999987</td>\n",
       "      <td>49815090</td>\n",
       "      <td>49815090</td>\n",
       "      <td>2145-11-03 08:47:00</td>\n",
       "      <td>files/p1999/p19999987/s49815090/49815090</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800035 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        subject_id  study_id  file_name            ecg_time  \\\n",
       "0         10000032  40689238   40689238 2180-07-23 08:44:00   \n",
       "1         10000032  44458630   44458630 2180-07-23 09:54:00   \n",
       "2         10000032  49036311   49036311 2180-08-06 09:07:00   \n",
       "3         10000117  45090959   45090959 2181-03-04 17:14:00   \n",
       "4         10000117  48446569   48446569 2183-09-18 13:52:00   \n",
       "...            ...       ...        ...                 ...   \n",
       "800030    19999840  48683947   48683947 2164-09-12 12:28:00   \n",
       "800031    19999840  41842293   41842293 2164-09-17 11:31:00   \n",
       "800032    19999987  41190887   41190887 2145-11-02 19:54:00   \n",
       "800033    19999987  45828463   45828463 2145-11-03 03:00:00   \n",
       "800034    19999987  49815090   49815090 2145-11-03 08:47:00   \n",
       "\n",
       "                                            path  path_exists  \n",
       "0       files/p1000/p10000032/s40689238/40689238        False  \n",
       "1       files/p1000/p10000032/s44458630/44458630        False  \n",
       "2       files/p1000/p10000032/s49036311/49036311        False  \n",
       "3       files/p1000/p10000117/s45090959/45090959        False  \n",
       "4       files/p1000/p10000117/s48446569/48446569        False  \n",
       "...                                          ...          ...  \n",
       "800030  files/p1999/p19999840/s48683947/48683947        False  \n",
       "800031  files/p1999/p19999840/s41842293/41842293        False  \n",
       "800032  files/p1999/p19999987/s41190887/41190887        False  \n",
       "800033  files/p1999/p19999987/s45828463/45828463        False  \n",
       "800034  files/p1999/p19999987/s49815090/49815090        False  \n",
       "\n",
       "[800035 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert ecg_time to datetime format\n",
    "machine_measurements['ecg_time'] = pd.to_datetime(machine_measurements['ecg_time'], errors='coerce')\n",
    "record_list['ecg_time'] = pd.to_datetime(record_list['ecg_time'], errors='coerce')\n",
    "\n",
    "# Check for missing values\n",
    "print(\"\\nMissing values in Machine Measurements:\")\n",
    "display(machine_measurements.isnull().sum())\n",
    "\n",
    "print(\"\\nMissing values in Record List:\")\n",
    "display(record_list.isnull().sum())\n",
    "\n",
    "# Check if paths in record_list exist\n",
    "record_list['path_exists'] = record_list['path'].apply(lambda x: os.path.exists(x))\n",
    "missing_paths = record_list[~record_list['path_exists']]\n",
    "\n",
    "# Report missing paths, if any\n",
    "if not missing_paths.empty:\n",
    "    print(\"\\nMissing paths in Record List:\")\n",
    "    display(missing_paths)\n",
    "else:\n",
    "    print(\"\\nAll file paths in Record List exist.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Merged Dataset Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 782185 entries, 0 to 782184\n",
      "Data columns (total 36 columns):\n",
      " #   Column       Non-Null Count   Dtype         \n",
      "---  ------       --------------   -----         \n",
      " 0   subject_id   782185 non-null  int64         \n",
      " 1   study_id     782185 non-null  int64         \n",
      " 2   file_name    782185 non-null  int64         \n",
      " 3   ecg_time     782185 non-null  datetime64[ns]\n",
      " 4   path         782185 non-null  object        \n",
      " 5   path_exists  782185 non-null  bool          \n",
      " 6   cart_id      782185 non-null  int64         \n",
      " 7   report_0     782184 non-null  object        \n",
      " 8   report_1     587755 non-null  object        \n",
      " 9   report_2     514119 non-null  object        \n",
      " 10  report_3     384746 non-null  object        \n",
      " 11  report_4     222511 non-null  object        \n",
      " 12  report_5     119528 non-null  object        \n",
      " 13  report_6     54903 non-null   object        \n",
      " 14  report_7     21843 non-null   object        \n",
      " 15  report_8     7119 non-null    object        \n",
      " 16  report_9     2280 non-null    object        \n",
      " 17  report_10    887 non-null     object        \n",
      " 18  report_11    394 non-null     object        \n",
      " 19  report_12    191 non-null     object        \n",
      " 20  report_13    102 non-null     object        \n",
      " 21  report_14    42 non-null      object        \n",
      " 22  report_15    19 non-null      object        \n",
      " 23  report_16    11 non-null      object        \n",
      " 24  report_17    3 non-null       object        \n",
      " 25  bandwidth    782185 non-null  object        \n",
      " 26  filtering    782185 non-null  object        \n",
      " 27  rr_interval  782185 non-null  int64         \n",
      " 28  p_onset      782185 non-null  int64         \n",
      " 29  p_end        782185 non-null  int64         \n",
      " 30  qrs_onset    782185 non-null  int64         \n",
      " 31  qrs_end      782185 non-null  int64         \n",
      " 32  t_end        782185 non-null  int64         \n",
      " 33  p_axis       782185 non-null  int64         \n",
      " 34  qrs_axis     782185 non-null  int64         \n",
      " 35  t_axis       782185 non-null  int64         \n",
      "dtypes: bool(1), datetime64[ns](1), int64(13), object(21)\n",
      "memory usage: 209.6+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "None"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>subject_id</th>\n",
       "      <th>study_id</th>\n",
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       "      <td>6376932</td>\n",
       "      <td>Sinus tachycardia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Normal ECG except for rate</td>\n",
       "      <td>...</td>\n",
       "      <td>60 Hz notch Baseline filter</td>\n",
       "      <td>600</td>\n",
       "      <td>40</td>\n",
       "      <td>130</td>\n",
       "      <td>162</td>\n",
       "      <td>244</td>\n",
       "      <td>474</td>\n",
       "      <td>79</td>\n",
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       "      <th>3</th>\n",
       "      <td>10000117</td>\n",
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       "      <td>2181-03-04 17:14:00</td>\n",
       "      <td>files/p1000/p10000117/s45090959/45090959</td>\n",
       "      <td>False</td>\n",
       "      <td>6214760</td>\n",
       "      <td>Sinus rhythm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Normal ECG</td>\n",
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       "      <td>60 Hz notch Baseline filter</td>\n",
       "      <td>659</td>\n",
       "      <td>40</td>\n",
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       "      <th>4</th>\n",
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       "      <td>48446569</td>\n",
       "      <td>48446569</td>\n",
       "      <td>2183-09-18 13:52:00</td>\n",
       "      <td>files/p1000/p10000117/s48446569/48446569</td>\n",
       "      <td>False</td>\n",
       "      <td>6632385</td>\n",
       "      <td>Sinus rhythm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   subject_id  study_id  file_name            ecg_time  \\\n",
       "0    10000032  40689238   40689238 2180-07-23 08:44:00   \n",
       "1    10000032  44458630   44458630 2180-07-23 09:54:00   \n",
       "2    10000032  49036311   49036311 2180-08-06 09:07:00   \n",
       "3    10000117  45090959   45090959 2181-03-04 17:14:00   \n",
       "4    10000117  48446569   48446569 2183-09-18 13:52:00   \n",
       "\n",
       "                                       path  path_exists  cart_id  \\\n",
       "0  files/p1000/p10000032/s40689238/40689238        False  6848296   \n",
       "1  files/p1000/p10000032/s44458630/44458630        False  6848296   \n",
       "2  files/p1000/p10000032/s49036311/49036311        False  6376932   \n",
       "3  files/p1000/p10000117/s45090959/45090959        False  6214760   \n",
       "4  files/p1000/p10000117/s48446569/48446569        False  6632385   \n",
       "\n",
       "            report_0                           report_1  \\\n",
       "0       Sinus rhythm  Possible right atrial abnormality   \n",
       "1       Sinus rhythm  Possible right atrial abnormality   \n",
       "2  Sinus tachycardia                                NaN   \n",
       "3       Sinus rhythm                                NaN   \n",
       "4       Sinus rhythm                                NaN   \n",
       "\n",
       "                     report_2  ...                    filtering rr_interval  \\\n",
       "0                         NaN  ...  60 Hz notch Baseline filter         659   \n",
       "1                         NaN  ...  60 Hz notch Baseline filter         722   \n",
       "2  Normal ECG except for rate  ...  60 Hz notch Baseline filter         600   \n",
       "3                  Normal ECG  ...  60 Hz notch Baseline filter         659   \n",
       "4                         NaN  ...              <not specified>         659   \n",
       "\n",
       "  p_onset  p_end qrs_onset qrs_end t_end p_axis qrs_axis t_axis  \n",
       "0      40    128       170     258   518     81       77     79  \n",
       "1      40    124       162     246   504     77       75     70  \n",
       "2      40    130       162     244   474     79       72     77  \n",
       "3      40    146       180     254   538     79       66     69  \n",
       "4     368  29999       504     590   868     84       80     77  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "PermissionError",
     "evalue": "[Errno 13] Permission denied: 'merged_ecg_data.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32mg:\\mimic-iv-ecg-diagnostic-electrocardiogram-matched-subset-1.0\\ECG_Analysis.ipynb Cell 4\u001b[0m line \u001b[0;36m1\n\u001b[0;32m     <a href='vscode-notebook-cell:/g%3A/mimic-iv-ecg-diagnostic-electrocardiogram-matched-subset-1.0/ECG_Analysis.ipynb#W3sZmlsZQ%3D%3D?line=13'>14</a>\u001b[0m \u001b[39m# Save merged dataset\u001b[39;00m\n\u001b[0;32m     <a href='vscode-notebook-cell:/g%3A/mimic-iv-ecg-diagnostic-electrocardiogram-matched-subset-1.0/ECG_Analysis.ipynb#W3sZmlsZQ%3D%3D?line=14'>15</a>\u001b[0m merged_output_path \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mmerged_ecg_data.csv\u001b[39m\u001b[39m\"\u001b[39m  \u001b[39m# Output file path\u001b[39;00m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/g%3A/mimic-iv-ecg-diagnostic-electrocardiogram-matched-subset-1.0/ECG_Analysis.ipynb#W3sZmlsZQ%3D%3D?line=15'>16</a>\u001b[0m merged_data\u001b[39m.\u001b[39;49mto_csv(merged_output_path, index\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n\u001b[0;32m     <a href='vscode-notebook-cell:/g%3A/mimic-iv-ecg-diagnostic-electrocardiogram-matched-subset-1.0/ECG_Analysis.ipynb#W3sZmlsZQ%3D%3D?line=16'>17</a>\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mMerged dataset saved to \u001b[39m\u001b[39m{\u001b[39;00mmerged_output_path\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n",
      "File \u001b[1;32mc:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\pandas\\util\\_decorators.py:333\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    327\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(args) \u001b[39m>\u001b[39m num_allow_args:\n\u001b[0;32m    328\u001b[0m     warnings\u001b[39m.\u001b[39mwarn(\n\u001b[0;32m    329\u001b[0m         msg\u001b[39m.\u001b[39mformat(arguments\u001b[39m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[0;32m    330\u001b[0m         \u001b[39mFutureWarning\u001b[39;00m,\n\u001b[0;32m    331\u001b[0m         stacklevel\u001b[39m=\u001b[39mfind_stack_level(),\n\u001b[0;32m    332\u001b[0m     )\n\u001b[1;32m--> 333\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
      "File \u001b[1;32mc:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\pandas\\core\\generic.py:3967\u001b[0m, in \u001b[0;36mNDFrame.to_csv\u001b[1;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[0;32m   3956\u001b[0m df \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(\u001b[39mself\u001b[39m, ABCDataFrame) \u001b[39melse\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mto_frame()\n\u001b[0;32m   3958\u001b[0m formatter \u001b[39m=\u001b[39m DataFrameFormatter(\n\u001b[0;32m   3959\u001b[0m     frame\u001b[39m=\u001b[39mdf,\n\u001b[0;32m   3960\u001b[0m     header\u001b[39m=\u001b[39mheader,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   3964\u001b[0m     decimal\u001b[39m=\u001b[39mdecimal,\n\u001b[0;32m   3965\u001b[0m )\n\u001b[1;32m-> 3967\u001b[0m \u001b[39mreturn\u001b[39;00m DataFrameRenderer(formatter)\u001b[39m.\u001b[39;49mto_csv(\n\u001b[0;32m   3968\u001b[0m     path_or_buf,\n\u001b[0;32m   3969\u001b[0m     lineterminator\u001b[39m=\u001b[39;49mlineterminator,\n\u001b[0;32m   3970\u001b[0m     sep\u001b[39m=\u001b[39;49msep,\n\u001b[0;32m   3971\u001b[0m     encoding\u001b[39m=\u001b[39;49mencoding,\n\u001b[0;32m   3972\u001b[0m     errors\u001b[39m=\u001b[39;49merrors,\n\u001b[0;32m   3973\u001b[0m     compression\u001b[39m=\u001b[39;49mcompression,\n\u001b[0;32m   3974\u001b[0m     quoting\u001b[39m=\u001b[39;49mquoting,\n\u001b[0;32m   3975\u001b[0m     columns\u001b[39m=\u001b[39;49mcolumns,\n\u001b[0;32m   3976\u001b[0m     index_label\u001b[39m=\u001b[39;49mindex_label,\n\u001b[0;32m   3977\u001b[0m     mode\u001b[39m=\u001b[39;49mmode,\n\u001b[0;32m   3978\u001b[0m     chunksize\u001b[39m=\u001b[39;49mchunksize,\n\u001b[0;32m   3979\u001b[0m     quotechar\u001b[39m=\u001b[39;49mquotechar,\n\u001b[0;32m   3980\u001b[0m     date_format\u001b[39m=\u001b[39;49mdate_format,\n\u001b[0;32m   3981\u001b[0m     doublequote\u001b[39m=\u001b[39;49mdoublequote,\n\u001b[0;32m   3982\u001b[0m     escapechar\u001b[39m=\u001b[39;49mescapechar,\n\u001b[0;32m   3983\u001b[0m     storage_options\u001b[39m=\u001b[39;49mstorage_options,\n\u001b[0;32m   3984\u001b[0m )\n",
      "File \u001b[1;32mc:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\pandas\\io\\formats\\format.py:1014\u001b[0m, in \u001b[0;36mDataFrameRenderer.to_csv\u001b[1;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[0;32m    993\u001b[0m     created_buffer \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[0;32m    995\u001b[0m csv_formatter \u001b[39m=\u001b[39m CSVFormatter(\n\u001b[0;32m    996\u001b[0m     path_or_buf\u001b[39m=\u001b[39mpath_or_buf,\n\u001b[0;32m    997\u001b[0m     lineterminator\u001b[39m=\u001b[39mlineterminator,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1012\u001b[0m     formatter\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfmt,\n\u001b[0;32m   1013\u001b[0m )\n\u001b[1;32m-> 1014\u001b[0m csv_formatter\u001b[39m.\u001b[39;49msave()\n\u001b[0;32m   1016\u001b[0m \u001b[39mif\u001b[39;00m created_buffer:\n\u001b[0;32m   1017\u001b[0m     \u001b[39massert\u001b[39;00m \u001b[39misinstance\u001b[39m(path_or_buf, StringIO)\n",
      "File \u001b[1;32mc:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\pandas\\io\\formats\\csvs.py:251\u001b[0m, in \u001b[0;36mCSVFormatter.save\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    247\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m    248\u001b[0m \u001b[39mCreate the writer & save.\u001b[39;00m\n\u001b[0;32m    249\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m    250\u001b[0m \u001b[39m# apply compression and byte/text conversion\u001b[39;00m\n\u001b[1;32m--> 251\u001b[0m \u001b[39mwith\u001b[39;00m get_handle(\n\u001b[0;32m    252\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfilepath_or_buffer,\n\u001b[0;32m    253\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmode,\n\u001b[0;32m    254\u001b[0m     encoding\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mencoding,\n\u001b[0;32m    255\u001b[0m     errors\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49merrors,\n\u001b[0;32m    256\u001b[0m     compression\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mcompression,\n\u001b[0;32m    257\u001b[0m     storage_options\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mstorage_options,\n\u001b[0;32m    258\u001b[0m ) \u001b[39mas\u001b[39;00m handles:\n\u001b[0;32m    259\u001b[0m     \u001b[39m# Note: self.encoding is irrelevant here\u001b[39;00m\n\u001b[0;32m    260\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mwriter \u001b[39m=\u001b[39m csvlib\u001b[39m.\u001b[39mwriter(\n\u001b[0;32m    261\u001b[0m         handles\u001b[39m.\u001b[39mhandle,\n\u001b[0;32m    262\u001b[0m         lineterminator\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlineterminator,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    267\u001b[0m         quotechar\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mquotechar,\n\u001b[0;32m    268\u001b[0m     )\n\u001b[0;32m    270\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_save()\n",
      "File \u001b[1;32mc:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\pandas\\io\\common.py:873\u001b[0m, in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m    868\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(handle, \u001b[39mstr\u001b[39m):\n\u001b[0;32m    869\u001b[0m     \u001b[39m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[0;32m    870\u001b[0m     \u001b[39m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[0;32m    871\u001b[0m     \u001b[39mif\u001b[39;00m ioargs\u001b[39m.\u001b[39mencoding \u001b[39mand\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m ioargs\u001b[39m.\u001b[39mmode:\n\u001b[0;32m    872\u001b[0m         \u001b[39m# Encoding\u001b[39;00m\n\u001b[1;32m--> 873\u001b[0m         handle \u001b[39m=\u001b[39m \u001b[39mopen\u001b[39;49m(\n\u001b[0;32m    874\u001b[0m             handle,\n\u001b[0;32m    875\u001b[0m             ioargs\u001b[39m.\u001b[39;49mmode,\n\u001b[0;32m    876\u001b[0m             encoding\u001b[39m=\u001b[39;49mioargs\u001b[39m.\u001b[39;49mencoding,\n\u001b[0;32m    877\u001b[0m             errors\u001b[39m=\u001b[39;49merrors,\n\u001b[0;32m    878\u001b[0m             newline\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[0;32m    879\u001b[0m         )\n\u001b[0;32m    880\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m    881\u001b[0m         \u001b[39m# Binary mode\u001b[39;00m\n\u001b[0;32m    882\u001b[0m         handle \u001b[39m=\u001b[39m \u001b[39mopen\u001b[39m(handle, ioargs\u001b[39m.\u001b[39mmode)\n",
      "\u001b[1;31mPermissionError\u001b[0m: [Errno 13] Permission denied: 'merged_ecg_data.csv'"
     ]
    }
   ],
   "source": [
    "# Merge machine_measurements and record_list on subject_id, study_id, and ecg_time\n",
    "merged_data = pd.merge(\n",
    "    record_list,\n",
    "    machine_measurements,\n",
    "    on=['subject_id', 'study_id', 'ecg_time'],\n",
    "    how='inner'\n",
    ")\n",
    "\n",
    "# Display information and preview merged data\n",
    "print(\"Merged Dataset Info:\")\n",
    "display(merged_data.info())\n",
    "display(merged_data.head())\n",
    "\n",
    "# Save merged dataset\n",
    "merged_output_path = \"merged_ecg_data.csv\"  # Output file path\n",
    "merged_data.to_csv(merged_output_path, index=False)\n",
    "print(f\"Merged dataset saved to {merged_output_path}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot RR intervals\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(merged_data['rr_interval'].dropna(), bins=30, color='skyblue', edgecolor='black')\n",
    "plt.title('Distribution of RR Intervals')\n",
    "plt.xlabel('RR Interval (ms)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of QRS vs. T axes\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(merged_data['qrs_axis'], merged_data['t_axis'], alpha=0.7, color='purple')\n",
    "plt.title('QRS Axis vs. T Axis')\n",
    "plt.xlabel('QRS Axis (degrees)')\n",
    "plt.ylabel('T Axis (degrees)')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Temp\\ipykernel_18912\\2543807873.py:9: DtypeWarning: Columns (16,17,18,19,20,21) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv(\"machine_measurements.csv\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape: (640028, 8), X_test shape: (160007, 8)\n",
      "y_train shape: (640028,), y_test shape: (160007,)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# Load the dataset\n",
    "df = pd.read_csv(\"machine_measurements.csv\")\n",
    "\n",
    "# Ensure necessary columns exist\n",
    "required_columns = ['qrs_onset', 'qrs_end', 'rr_interval', 'p_onset', 'p_end', 'p_axis', 'qrs_axis', 't_axis']\n",
    "for col in required_columns:\n",
    "    if col not in df.columns:\n",
    "        raise ValueError(f\"Missing column: {col}\")\n",
    "\n",
    "# Compute QRS duration\n",
    "df['qrs_duration'] = df['qrs_end'] - df['qrs_onset']\n",
    "\n",
    "# Encode WCT Labels\n",
    "df['wct_label'] = np.where(df['qrs_duration'] > 120, 'WCT', 'Normal')\n",
    "\n",
    "# Apply Label Encoding\n",
    "label_encoder = LabelEncoder()\n",
    "df['wct_label_encoded'] = label_encoder.fit_transform(df['wct_label'])\n",
    "\n",
    "# Select Features and Target Variable\n",
    "features = ['rr_interval', 'p_onset', 'p_end', 'qrs_onset', 'qrs_end', 'p_axis', 'qrs_axis', 't_axis']\n",
    "X = df[features].dropna()  # Remove NaN rows\n",
    "y = df.loc[X.index, 'wct_label_encoded']  # Ensure index consistency\n",
    "\n",
    "# Split the dataset\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Display dataset shapes\n",
    "print(f\"X_train shape: {X_train.shape}, X_test shape: {X_test.shape}\")\n",
    "print(f\"y_train shape: {y_train.shape}, y_test shape: {y_test.shape}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   subject_id  study_id  cart_id           ecg_time_x           report_0  \\\n",
      "0    10000032  40689238  6848296  2180-07-23 08:44:00       Sinus rhythm   \n",
      "1    10000032  44458630  6848296  2180-07-23 09:54:00       Sinus rhythm   \n",
      "2    10000032  49036311  6376932  2180-08-06 09:07:00  Sinus tachycardia   \n",
      "3    10000117  45090959  6214760  2181-03-04 17:14:00       Sinus rhythm   \n",
      "4    10000117  48446569  6632385  2183-09-18 13:52:00       Sinus rhythm   \n",
      "\n",
      "                            report_1                    report_2  \\\n",
      "0  Possible right atrial abnormality                         NaN   \n",
      "1  Possible right atrial abnormality                         NaN   \n",
      "2                                NaN  Normal ECG except for rate   \n",
      "3                                NaN                  Normal ECG   \n",
      "4                                NaN                         NaN   \n",
      "\n",
      "         report_3 report_4 report_5  ... t_end p_axis qrs_axis t_axis  \\\n",
      "0  Borderline ECG      NaN      NaN  ...   518     81       77     79   \n",
      "1  Borderline ECG      NaN      NaN  ...   504     77       75     70   \n",
      "2             NaN      NaN      NaN  ...   474     79       72     77   \n",
      "3             NaN      NaN      NaN  ...   538     79       66     69   \n",
      "4             NaN      NaN      NaN  ...   868     84       80     77   \n",
      "\n",
      "  qrs_duration wct_label wct_label_encoded file_name           ecg_time_y  \\\n",
      "0           88    Normal                 0  40689238  2180-07-23 08:44:00   \n",
      "1           84    Normal                 0  44458630  2180-07-23 09:54:00   \n",
      "2           82    Normal                 0  49036311  2180-08-06 09:07:00   \n",
      "3           74    Normal                 0  45090959  2181-03-04 17:14:00   \n",
      "4           86    Normal                 0  48446569  2183-09-18 13:52:00   \n",
      "\n",
      "                                       path  \n",
      "0  files/p1000/p10000032/s40689238/40689238  \n",
      "1  files/p1000/p10000032/s44458630/44458630  \n",
      "2  files/p1000/p10000032/s49036311/49036311  \n",
      "3  files/p1000/p10000117/s45090959/45090959  \n",
      "4  files/p1000/p10000117/s48446569/48446569  \n",
      "\n",
      "[5 rows x 39 columns]\n",
      "Merged ECG Data Saved Successfully!\n"
     ]
    }
   ],
   "source": [
    "# Load the ECG records file\n",
    "df_records = pd.read_csv(\"record_list.csv\")\n",
    "\n",
    "# Ensure necessary columns exist\n",
    "required_columns_records = ['subject_id', 'study_id', 'file_name', 'ecg_time', 'path']\n",
    "for col in required_columns_records:\n",
    "    if col not in df_records.columns:\n",
    "        raise ValueError(f\"Missing column: {col}\")\n",
    "\n",
    "# Merge ECG metadata with machine_measurements.csv based on subject_id and study_id\n",
    "df_merged = df.merge(df_records, on=['subject_id', 'study_id'], how='left')\n",
    "\n",
    "# Display merged dataset preview\n",
    "print(df_merged.head())\n",
    "\n",
    "# Save merged file for further processing\n",
    "df_merged.to_csv(\"merged_ecg_data.csv\", index=False)\n",
    "print(\"Merged ECG Data Saved Successfully!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select only numeric features\n",
    "correlation_features = ['rr_interval', 'p_onset', 'p_end', 'qrs_onset', 'qrs_end', 'qrs_duration', 'p_axis', 'qrs_axis', 't_axis']\n",
    "corr_matrix = df[correlation_features].corr()\n",
    "\n",
    "# Plot heatmap\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(corr_matrix, annot=True, cmap=\"coolwarm\", fmt=\".2f\")\n",
    "plt.title(\"ECG Feature Correlation Heatmap\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Temp\\ipykernel_18912\\139207884.py:7: DtypeWarning: Columns (16,17,18,19,20,21) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  measurements_df = pd.read_csv('machine_measurements.csv')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "# Load CSV Files\n",
    "measurements_df = pd.read_csv('machine_measurements.csv')\n",
    "record_list_df = pd.read_csv('record_list.csv')\n",
    "\n",
    "# Ensure we have only valid numerical data\n",
    "features = ['rr_interval', 'p_onset', 'p_end', 'qrs_onset', 'qrs_end', 'p_axis', 'qrs_axis', 't_axis']\n",
    "df_filtered = measurements_df.dropna(subset=features)\n",
    "\n",
    "# Select a subset of data for visualization\n",
    "num_samples = 100  \n",
    "df_sample = df_filtered.sample(n=num_samples, random_state=42)\n",
    "\n",
    "# Extract ECG-based motion components\n",
    "X = df_sample['p_onset'].values  # X-axis (time of P-wave onset)\n",
    "Y = df_sample['qrs_onset'].values  # Y-axis (time of QRS onset)\n",
    "Z = df_sample['t_axis'].values  # Z-axis (electrical axis of T-wave)\n",
    "\n",
    "# Generate motion vectors\n",
    "U = df_sample['rr_interval'].values / 100  # Normalize for scaling\n",
    "V = df_sample['p_end'].values / 100\n",
    "W = df_sample['qrs_axis'].values / 100\n",
    "\n",
    "# Plot the 3D scatter points and motion vectors\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "# Red Dots - Representing ECG Data Points\n",
    "ax.scatter(X, Y, Z, color='red', s=5, label=\"ECG Data Points\")\n",
    "\n",
    "# Blue Motion Vectors\n",
    "ax.quiver(X, Y, Z, U, V, W, color='blue', length=2, normalize=True)\n",
    "\n",
    "# Axis Labels\n",
    "ax.set_xlabel(\"P Onset (ms)\")\n",
    "ax.set_ylabel(\"QRS Onset (ms)\")\n",
    "ax.set_zlabel(\"T Axis (degrees)\")\n",
    "\n",
    "# Title\n",
    "ax.set_title(\"3D ECG Motion Vectors for Wide QRS Complex Tachycardia\")\n",
    "\n",
    "# Show Plot\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Temp\\ipykernel_18912\\2048896283.py:8: DtypeWarning: Columns (16,17,18,19,20,21) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  measurements_df = pd.read_csv('machine_measurements.csv')\n",
      "C:\\Users\\MR. VASKAR CHAKMA\\AppData\\Local\\Temp\\ipykernel_18912\\2048896283.py:56: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  plt.tight_layout(rect=[0, 0.1, 1, 0.95])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 11 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import Normalize\n",
    "import matplotlib.cm as cm\n",
    "\n",
    "# Load CSV Files\n",
    "measurements_df = pd.read_csv('machine_measurements.csv')\n",
    "record_list_df = pd.read_csv('record_list.csv')\n",
    "\n",
    "# Ensure we have only valid numerical data\n",
    "features = ['rr_interval', 'p_onset', 'p_end', 'qrs_onset', 'qrs_end', 'p_axis', 'qrs_axis', 't_axis']\n",
    "df_filtered = measurements_df.dropna(subset=features)\n",
    "\n",
    "# Select a subset of data for visualization (e.g., 10 patients)\n",
    "num_patients = 10\n",
    "df_sample = df_filtered.sample(n=num_patients, random_state=42)\n",
    "\n",
    "# Bullseye Plot Configuration\n",
    "num_segments = 17  # Standard heart segmentation\n",
    "theta = np.linspace(0, 2 * np.pi, num_segments + 1)\n",
    "radii = [0.2, 0.4, 0.6, 0.8, 1.0]  # Circular region levels\n",
    "\n",
    "# Normalize motion data for colormap\n",
    "motion_values = df_sample['rr_interval'].values\n",
    "norm = Normalize(vmin=min(motion_values), vmax=max(motion_values))\n",
    "cmap = cm.coolwarm  # Blue-to-purple colormap\n",
    "\n",
    "# Create a figure with multiple patient plots\n",
    "fig, axes = plt.subplots(2, 5, figsize=(15, 6), subplot_kw={'projection': 'polar'})\n",
    "\n",
    "for i, ax in enumerate(axes.flatten()):\n",
    "    if i >= num_patients:\n",
    "        ax.axis('off')\n",
    "        continue\n",
    "\n",
    "    # Plot each segment with motion intensity\n",
    "    for j, radius in enumerate(radii[:-1]):\n",
    "        ax.fill_between(theta, radius, radii[j+1], color=cmap(norm(motion_values[i])), alpha=0.8)\n",
    "\n",
    "    # Mark lead tips (red dots)\n",
    "    ax.scatter(theta[:-1][::4], np.full_like(theta[:-1][::4], 1.05), color='red', s=20)\n",
    "\n",
    "    # Labels\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    ax.set_title(f'Patient {i+1}', fontsize=12)\n",
    "\n",
    "# Add Colorbar\n",
    "cbar_ax = fig.add_axes([0.3, 0.1, 0.4, 0.03])\n",
    "sm = cm.ScalarMappable(cmap=cmap, norm=norm)\n",
    "fig.colorbar(sm, cax=cbar_ax, orientation='horizontal', label=\"Motion [mm]\")\n",
    "\n",
    "# Show Plot\n",
    "plt.suptitle(\"ECG Motion Bullseye Plot for Multiple Patients\", fontsize=14)\n",
    "plt.tight_layout(rect=[0, 0.1, 1, 0.95])\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
